Gender: Female 
Age: 45-54
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Divorced 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 9
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Exercise 
Devices used daily: Laptop;Smartphone;Smartwatch;Tablet 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Grammar checker (i.e., correcting grammar mistakes) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;Google Gemini 
LLM use cases: Coding;Writing (e.g., composing emails);Solving math or logical problems;Proofreading/Editing (e.g., grammar, spelling, structure improvements) 
Contexts of LLM use: Technical;Work 
Prompt 1: Explain how engagement positively influences outcomes such as job satisfaction, performance, innovation, retention, and organizational culture.
Prompt 2: Describe the behaviors, attitudes, and traits commonly found in engaged employees.
Prompt 3:  Benefits of an Engaged Employee/Workforce
Prompt 4: What is the significance of IFRS adoption on financial reporting quality from a country comparison perspective, considering key dependent and independent variables?
Prompt 5: What economic, regulatory, and institutional characteristics influence a country’s decision to not adopt, partially adopt, or fully adopt IFRS?
Prompt 6: How does IFRS adoption impact financial report comparability, considering factors such as accounting policy consistency, disclosure practices, and earnings management pre-adoption and post-adoption?
Prompt 7: What country-specific barriers, such as legal frameworks, enforcement mechanisms, and professional expertise, affect IFRS implementation and the quality of financial reporting?
Prompt 8: If you had to explain recursion to a five-year-old, how would you do it?
Prompt 9: In your opinion, what makes a great leader?
Prompt 10: If you could redesign one everyday object to be more efficient, what would it be and why?
Comments: Not Really.